Kudella Patrick Wolfgang, Moll Kirsten, Wahlgren Mats, Wixforth Achim, Westerhausen Christoph
Experimental Physics I, University of Augsburg, Universitätsstraße 1, Augsburg, Germany.
Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Box 280, 171 77, Stockholm, Sweden.
Malar J. 2016 Apr 18;15:223. doi: 10.1186/s12936-016-1243-4.
Rosetting is associated with severe malaria and a primary cause of death in Plasmodium falciparum infections. Detailed understanding of this adhesive phenomenon may enable the development of new therapies interfering with rosette formation. For this, it is crucial to determine parameters such as rosetting and parasitaemia of laboratory strains or patient isolates, a bottleneck in malaria research due to the time consuming and error prone manual analysis of specimens. Here, the automated, free, stand-alone analysis software automated rosetting analyzer for micrographs (ARAM) to determine rosetting rate, rosette size distribution as well as parasitaemia with a convenient graphical user interface is presented.
Automated rosetting analyzer for micrographs is an executable with two operation modes for automated identification of objects on images. The default mode detects red blood cells and fluorescently labelled parasitized red blood cells by combining an intensity-gradient with a threshold filter. The second mode determines object location and size distribution from a single contrast method. The obtained results are compared with standardized manual analysis. Automated rosetting analyzer for micrographs calculates statistical confidence probabilities for rosetting rate and parasitaemia.
Automated rosetting analyzer for micrographs analyses 25 cell objects per second reliably delivering identical results compared to manual analysis. For the first time rosette size distribution is determined in a precise and quantitative manner employing ARAM in combination with established inhibition tests. Additionally ARAM measures the essential observables parasitaemia, rosetting rate and size as well as location of all detected objects and provides confidence intervals for the determined observables. No other existing software solution offers this range of function. The second, non-malaria specific, analysis mode of ARAM offers the functionality to detect arbitrary objects.
Automated rosetting analyzer for micrographs has the capability to push malaria research to a more quantitative and statistically significant level with increased reliability due to operator independence. As an installation file for Windows © 7, 8.1 and 10 is available for free, ARAM offers a novel open and easy-to-use platform for the malaria community to elucidate resetting.
红细胞凝集与严重疟疾相关，是恶性疟原虫感染导致死亡的主要原因。深入了解这种黏附现象可能有助于开发干扰红细胞凝集形成的新疗法。为此，确定实验室菌株或患者分离株的红细胞凝集和寄生虫血症等参数至关重要，而由于对标本进行手动分析既耗时又容易出错，这成为疟疾研究的一个瓶颈。在此，我们展示了一种自动化、免费的独立分析软件——显微图像自动红细胞凝集分析仪（ARAM），它具有便捷的图形用户界面，可用于确定红细胞凝集率、红细胞凝集大小分布以及寄生虫血症。
显微图像自动红细胞凝集分析仪是一个可执行程序，有两种操作模式用于自动识别图像上的物体。默认模式通过结合强度梯度和阈值滤波器来检测红细胞以及荧光标记的被寄生红细胞。第二种模式通过单一对比度方法确定物体位置和大小分布。将获得的结果与标准化手动分析进行比较。显微图像自动红细胞凝集分析仪计算红细胞凝集率和寄生虫血症的统计置信概率。
显微图像自动红细胞凝集分析仪每秒可可靠地分析25个细胞物体，与手动分析相比能得出相同结果。首次使用ARAM结合既定的抑制试验以精确和定量的方式确定红细胞凝集大小分布。此外，ARAM可测量关键的可观察指标寄生虫血症、红细胞凝集率和大小以及所有检测物体的位置，并为所确定的可观察指标提供置信区间。没有其他现有软件解决方案具备如此广泛的功能。ARAM的第二种非疟疾特异性分析模式具有检测任意物体的功能。
显微图像自动红细胞凝集分析仪有能力将疟疾研究提升到一个更具定量性和统计学意义的水平，由于其独立于操作人员，可靠性更高。作为适用于Windows © 7、8.1和10的安装文件可免费获取，ARAM为疟疾研究群体提供了一个新颖的、开放且易于使用的平台来阐明红细胞凝集现象。
